STA 364 Spring 2025
Exam 2 Outline
This in-class exam is worth 100 points. The take-home is worth 100 points.
Outline
Content in Exam 1 Outline HERE.
ETS Models
- Smoothing models with trend
- Smoothing models with seasonality
- Identifying when to use multiplicative models vs additive models
- Comparing models
- How
ETS()auto selection function works. - Given the forecast variance formula, \(\hat{\sigma}_h\), calculate the prediction interval.
- ARIMA Models
- Stationarity: Identify if a series is or is not stationary.
- Differencing: What is it? What kinds? Why?
- Backshift notation: What is it, and what does it do?
- Autoregressive Models (AR): Conditions, how to fit, model equation.
- Moving Average Models (MA): Conditions, how to fit, model equation.
- ARIMA Models: Write out the specific equation using the general equation and a 𝑝,𝑑, and 𝑞 (small) idenifying the orders (\(p\) and \(q\)) by looking at a stationary series’s correlogram and PACF plot.
- SARIMA Models: Same as ARIMA but with a season piece.
- ARIMA vs ETA
ARIMA()function default algorithm.
- Overall
- Fitting and comparing models on a test set
- Forecasting with all models
Codebank
You can also find the take home exam codebank by clicking HERE.